Evidence map›Paper›PMID 32083693›Full record

ArticleJAMA network open2020

Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia.

Chi-Shin Wu, Alex R Luedtke, Ekaterina Sadikova, Hui-Ju Tsai, Shih-Cheng Liao, Chen-Chung Liu, Susan Shur-Fen Gau, Tyler J VanderWeele, Ronald C Kessler

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 2 countries.

Chi-Shin WuDepartment of Psychiatry, National Taiwan University Hospital & College of Medicine, National Taiwan University, Taipei City, Taiwan.
Alex R LuedtkeDepartment of Statistics, University of Washington, Seattle.
Ekaterina SadikovaDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Hui-Ju TsaiInstitute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
Shih-Cheng LiaoDepartment of Psychiatry, National Taiwan University Hospital & College of Medicine, National Taiwan University, Taipei City, Taiwan.
Chen-Chung LiuDepartment of Psychiatry, National Taiwan University Hospital & College of Medicine, National Taiwan University, Taipei City, Taiwan.
Susan Shur-Fen GauDepartment of Psychiatry, National Taiwan University Hospital & College of Medicine, National Taiwan University, Taipei City, Taiwan.
Tyler J VanderWeeleDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Ronald C KesslerDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
National Taiwan University Hospital · TWHarvard University · USNational Health Research Institutes · TWUniversity of Washington · US

Funding

Theory and methods for mediation and interactionR01CA222147 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI TCHETGEN TCHETGEN, ERIC JOEL, VANDERWEELE, TYLER · 2018 to 2022
$2.1M
NCI NIH HHS R01 CA222147
6 · The paper itself

Abstract

Importance: Little guidance exists to date on how to select antipsychotic medications for patients with first-episode schizophrenia. Objective: To develop a preliminary individualized treatment rule (ITR) for patients with first-episode schizophrenia. Design, Setting, and Participants: This prognostic study obtained data from Taiwan's National Health Insurance Research Database on patients with prescribed antipsychotic medications, ambulatory claims, or discharge diagnoses of a schizophrenic disorder between January 1, 2005, and December 31, 2011. An ITR was developed by applying a targeted minimum loss-based ensemble machine learning method to predict treatment success from baseline clinical and demographic data in a 70% training sample. The model was validated in the remaining 30% of the sample. The probability of treatment success was estimated for each medication for each patient under the model. The analysis was conducted between July 16, 2018, and July 15, 2019. Exposures: Fifteen different antipsychotic medications. Main Outcomes and Measures: Treatment success was defined as not switching medication and not being hospitalized for 12 months. Results: Among the 32 277 patients in the analysis, the mean (SD) age was 36.7 (14.3) years, and 15 752 (48.8%) were male. In the validation sample, the treatment success rate (SE) was 51.7% (1.0%) under the ITR and was 44.5% (0.5%) in the observed population (Z = 7.1; P < .001). The estimated treatment success if all patients were given a prescription for 1 medication was significantly lower for each of the 13 medications than under the ITR (Z = 4.2-16.8; all P < .001). Aripiprazole (3088 [31.9%]) and amisulpride (2920 [30.2%]) were the medications most often recommended by the ITR. Only 1054 patients (10.9%) received ITR-recommended medications. Observed treatment success, although lower than the success under the ITR, was nonetheless significantly higher than if medications had been randomized (44.5% [SE, 0.55%] vs 41.3% [SE, 0.4%]; Z = 6.9; P < .001), although only marginally higher than if medications had been randomized in their observed population proportions (44.5% [SE, 0.5%] vs 43.5% [SE, 0.4%]; Z = 2.2; P = .03]). Conclusions and Relevance: These results suggest that an ITR may be associatded with an increase in the treatment success rate among patients with first-episode schizophrenia, but experimental evaluation is needed to confirm this possibility. If confirmed, model refinement that investigates biomarkers, clinical observations, and patient reports as additional predictors in iterative pragmatic trials would be needed before clinical implementation.

Indexed as

Clinical Decision RulesMachine LearningAdultAntipsychotic AgentsFemaleHumansMaleMiddle AgedModels, StatisticalPrecision MedicinePrognosisRetrospective StudiesSchizophreniaTreatment OutcomeYoung AdultAntipsychotic Agents

Identifiers

PMID32083693
PMCPMC7043195
OpenAlexW3007350806

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.